Urban Versus Rural Differences in Meeting 24‐h Movement Behaviour Guidelines Among 3–4‐Year‐Olds: An Analysis of SUNRISE Pilot Study Data From 10 Low‐ and Middle‐Income Countries
Bibliographic record
Abstract
BACKGROUND: Insufficient physical activity, excessive screen time and short sleep duration among young children are global public health concerns; however, data on prevalence of meeting World Health Organisation 24-h movement behaviour guidelines for 3-4-year-old children in low- and middle-income countries (LMICs) are limited, and it is unknown whether urbanisation is related to young children's movement behaviours. The present study examined differences in prevalence of meeting 24-h movement behaviour guidelines among 3-4-year-old children living in urban versus rural settings in LMICs. METHODS: The SUNRISE Study recruited 429, 3-4-year-old child/parent dyads from 10 LMICs. Children wore activPAL accelerometers continuously for at least 48 h to assess their physical activity and sleep duration. Screen time and time spent restrained were assessed via parent questionnaire. Differences in prevalence of meeting guidelines between urban- and rural-dwelling children were examined using chi-square tests. RESULTS: Physical activity guidelines were met by 17% of children (14% urban vs. 18% rural), sleep guidelines by 57% (61% urban vs. 54% rural), screen time guidelines by 50% (50% urban vs. 50% rural), restrained guidelines by 84% (81% urban vs. 86% rural) and all guidelines combined by 4% (4% urban vs.4% rural). We found no significant differences in meeting the guidelines between urban and rural areas. CONCLUSIONS: Only a small proportion of children in both rural and urban settings met the WHO 24-h movement guidelines. Strategies to improve movement behaviours in LMICs should consider including both rural and urban settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".